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Record W4210505661 · doi:10.1111/imig.12976

Who are Canada’s temporary foreign workers? Policy evolution and a pandemic reality

2022· article· en· W4210505661 on OpenAlex
Marshia Akbar

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Migration · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTemporary workContext (archaeology)CitizenshipWork (physics)InequalityPandemicEconomic shortagePolitical scienceSocial policyCoronavirus disease 2019 (COVID-19)Migrant workersDemographic economicsEconomic growthLabour economicsEconomicsGeographyLawMedicine

Abstract

fetched live from OpenAlex

Abstract Since the late‐2000s, Canada has admitted an increasing number of foreign workers with a wide range of temporary work permits to meet local labour shortages and growing labour market demands. Unlike permanent residents, temporary residents are subjected to restricted work authorizations and social citizenship rights. Besides, Canadian policies distinguish different groups of temporary foreign workers based on their skill level and work permit type to determine their eligibility for employment, social rights and permanent residency. Reviewing secondary sources, this paper contributes to analyzing the key policies that have shaped the diverse streams within the Canadian temporary migration program. The analysis also highlights the inequalities experienced by various categories of temporary foreign workers in Canada and assesses these inequalities within the context of the COVID‐19 pandemic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.297
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it